FPGA Central

#1 (**permalink**) 07-25-2005, 10:04 AM

Rune Allnor wrote:
>
> Kamran wrote:
>
>>Rune Allnor wrote:
>>
>>>Kamran wrote:
>>>
>>>
>>>>Hi
>>>>
>>>>
>>>>Could anyone help me on how to use lpc (linear prediction coeff)
>>>>for interpolation ? I have a vector where some elements(samples) are way
>>>>off what is reasonable and wondered if I could use lpc
>>>>to estimate replacements for those but I don't know how
>>>>to incorporate the neighbouring (those before and after)samples
>>>>to estimate the new ones. Matlab has a function called 'lpc'
>>>>but I am a bit confused how to use that (more than a bit)
>>>
>>>
>>>Here is one possible way, assuming there are only one bad
>>>sample per burst:
>>>
>>>- Build a signal autocovariance matrix from only good data
>>>- Estimate the order of the AR predictor that bes fits the
>>> signal statistic, call the order P.
>>>- Use the P samples preceeding each bad sample, and use the
>>> forward prediction estimator to find a "good" value for the
>>> bad sample
>>>- Repeat for the P samples following a bad sample, using the
>>> backward estimator
>>>- Estimate the "bad" sample as the average between the forward
>>> and backward predictions.
>>>
>>>Apart from that, go have a chat with Sverre Holm, who I think
>>>still is with your university.
>>>
>>>Rune
>>>
>>
>>Thanks Rune for the answer.
>>What I don't understand about matlab's 'lpc' is that
>>it gives me the same number of samples which are the
>>estimates of the existing samples and not the next sample
>>(missing one), the one I am looking for!
>>I have my own routine for linear prediction and I am trying
>>to compare that with matlab's 'lpc'.
>
>
> Eh... LPC computes the prediction coefficients from the available
> data, based on the estimated autocorrelation sequence. You ought to
> get the coefficients of the N'th order predictor by the call
>
> a=lpc(x,N);
>
> where x is the data vector. Once you have the prediction coefficients,
> you apply them in the usual way to the data.
>
> Rune
>

Thanks a lot Rune. I got it now.

Kamran

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